A challenge in designing image sensors is the need for the image sensor to exhibit a very wide dynamic range. Fields include general photography and video (cinematography, broadcast, personal photography, etc.), aerial photography (intelligence gathering), agricultural photography (crop analysis), product inspection, medical applications, and automotive applications. In many applications, particularly outdoor, the image sensor is required to have a wide dynamic range to account for very bright and very dark areas. Applications may have lighting conditions from below 1 lux for night vision to over 10,000 lux for bright sunlight. Real world scenes may have illumination intensities varying over a dB range of 100 or more. While biological vision systems and silver halide film can image high dynamic range (100+ dB) scenes with little loss of contrast information, it has been challenging to develop electronic image sensors with this range.
Most current image sensors have limited dynamic ranges, typically between 50 dB to 80 dB. Because of this, relevant information content of the captured scene is lost. Additionally, the large variation of illumination intensity can manifest itself in image blooming for scenes with very bright areas. The pixels illuminated by the very bright light saturate and flood signal onto adjacent pixels so that the bright areas of the output image grow and the true image is lost. CMOS image sensors generally suffer from poor image quality because CMOS image sensors generally have a low dynamic range in image capability. Conventional CMOS image sensors are capable of recording approximately 10 bits of a scene's dynamic range. Methods for improving the dynamic range of CMOS image sensors have been applied to improve the quality of the captured image. However, these methods do not meet the needs for ultrawide dynamic range (UDR) image sensors.
The challenge is to create a wide dynamic range image sensor having sufficient optical sensitivity in shadow areas where there is low illumination and sufficient sensitivity range for bright areas with high illumination, and for highlights with very bright illumination. To accomplish this requires having simultaneously very low noise for the low illumination and very low optical speed for high illumination. It is important that signal-to-noise behavior is good over the whole illumination range for a set of images making up a video stream.
What is needed is an improved ultra-high dynamic range (UDR) image sensor that can more accurately capture image scenes.